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首页> 外文学位 >AN ADAPTIVE DECISION MAKING METHODOLOGY FOR MATERIAL HANDLING EQUIPMENT IN A COMPUTER INTEGRATED MANUFACTURING SYSTEM (CIMS, ROBOT, OPERATIONAL).
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AN ADAPTIVE DECISION MAKING METHODOLOGY FOR MATERIAL HANDLING EQUIPMENT IN A COMPUTER INTEGRATED MANUFACTURING SYSTEM (CIMS, ROBOT, OPERATIONAL).

机译：计算机集成制造系统（CIMS，机器人，操作性）中材料处理设备的自适应决策方法。

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摘要

The design and operation of a robotic manufacturing system can be a complex task for which little experience is now available. This research has attempted to develop an operational control strategy for a computer integrated system with robots and other automated material handling equipment. The control strategy requires the integration of several software tools such as simulation, optimization, data base, pattern recognition, and robot control system. The integration has been developed in two levels which have different functions.; The first level will construct a model system which can support the control information for the real system operation. The basic components in this level consists of simulation, optimization, and a data base. Simulation was used as a flexible means to describe the large complex system. An Optimization algorithm helps such a simulation model to make good choices for control parameters. The data base was used to handle the extensive information.; The second level will control the hardware by using the information from the first level. The system control parameters can be updated on a periodic basis to account for the current shop load and pending orders. A nearest neighbor pattern recognition algorithm has been applied to retrieve the optimal control parameters.; The developed control strategy has shown significant improvement in some non-fixed input rate cases. The implementation of the strategy was validated through an on-line real time computer controlled robot.
机译：机器人制造系统的设计和操作可能是一项复杂的任务，目前尚缺乏经验。这项研究试图为带有机器人和其他自动物料搬运设备的计算机集成系统开发一种操作控制策略。控制策略需要集成多个软件工具，例如仿真，优化，数据库，模式识别和机器人控制系统。集成已开发成具有不同功能的两个级别。第一级将构建一个模型系统，该模型系统可以支持实际系统操作的控制信息。该级别的基本组件包括仿真，优化和数据库。仿真被用作描述大型复杂系统的灵活方式。优化算法有助于这种仿真模型为控制参数做出良好的选择。该数据库用于处理大量信息。第二级将通过使用来自第一级的信息来控制硬件。可以定期更新系统控制参数，以解决当前的车间负荷和挂单。最近邻居模式识别算法已被应用来检索最佳控制参数。在某些非固定输入速率情况下，已开发的控制策略已显示出显着改进。该策略的实施已通过在线实时计算机控制的机器人进行了验证。

著录项

  • 作者

    CHU, CHI-CHUNG.;

  • 作者单位

    Purdue University.;

  • 授予单位 Purdue University.;
  • 学科 Engineering Industrial.
  • 学位 Ph.D.
  • 年度 1984
  • 页码 171 p.
  • 总页数 171
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 一般工业技术;
  • 关键词

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